波浪作用下空心块体稳定性分析初探

通过二维物理模型试验,探讨了暗基床上空心块体在规则波作用下的失稳模式。通过试验观察发现,当空心块体内有一定高度的填料时,波浪正向作用下空心块体首先倾覆失稳。本试验测量了作用在空心块体上的波浪力,并与同尺寸沉箱所受的波浪力进行对比,结果显示在波峰时空心块体所受的总水平波浪力比相同波浪作用下的沉箱所受力小而波谷作用下空心块体所受的总水平波浪力却比相同波浪作用下的沉箱所受波浪力大。鉴于上述实验观察结果,空心块体的主要失稳模式分析方法应作进一步研究。     

复合材料四结点四边形多层退化壳单元

本文提出了一个复合材料四结点四边形多层退化壳单元。单元从修正的Hu-Washizu变分原理导出,独立假设位移场、每层内部应变场和应力场。文中给出了几个复合材料板和壳静力线性问题实例。计算结果表明本文的单元是准确和有效的。     

基于多模型半参数非线性回归模型的外弹道节省参数估计

双星定位系统的应用是外弹道估计中的一种发展趋势。文章给出基于双星、光雷的联合测量模型,建立基于半参数回归的外弹道节省参数估计模型;给出基于半参数回归的外弹道节省参数估计算法及计算步骤,并从理论上分析了基于半参数回归的外弹道节省参数估计算法能有效地消除非线性因素对参数估计性能的影响,其估计精度优于经典的节省参数建模方法,并通过仿真得到：该算法确实有效。     

面向Web Services的工作流管理系统设计

文章通过Web Services技术与工作流技术的结合,提供了Web Services对工作流系统建模和执行阶段的支持,设计了一个面向Web Services的工作流管理系统。利用以Web Services为基础的WS-BPEL工作流技术解决了当前工作流技术在不同企业间协作的互操作问题,从而实现了基于Internet的业务流程管理,为跨企业间的流程协作提出了一种新的解决方案。     

海表面盐度卫星微波遥感研究进展

海表面盐度SSS(Sea Surface Salinity)是研究大洋环流和海洋对全球气候影响的重要参量、是决定海水基本性质的重要因素之一。卫星微波遥感可以满足盐度研究过程中大范围、连续观测的需要,国际上统一的认识是选择频率为1.413 GHz的L波段作为盐度遥感的首选波段。目前,国外发展的海面盐度微波遥感反演算法主要有两种:基于海表发射率估算海表盐度的算法和基于贝叶斯定理提出的反演算法。影响盐度反演精度的因素主要有太空辐射、电离层法拉第旋转、大气、海面粗糙度等。其中,海面粗糙度对盐度反演影响很大,海面粗糙度处理模型可以分为3大类:理论算法(间接发射率模型、直接发射率模型)、经验算法、半经验半理论算法(Hollinger 半经验模型、WISE半经验模型、Gabarró模型)。SMOS卫星和Aquarius/SAC\|D卫星的成功发射,将海表面盐度遥感的反演精度控制在0.2 psu以内,通过改进反演算法,有望得到更高的反演精度。     

Monthly Streamflow Forecasting Using Convolutional Neural Network

Monthly streamflow forecasting is vital for managing water resources. Recently, numerous studies have explored and evidenced the potential of artificial intelligence (AI) models in hydrological forecasting. In this study, the feasibility of the convolutional neural network (CNN), a deep learning method, is explored for monthly streamflow forecasting. CNN can automatically extract critical features from numerous inputs with its convolution–pooling mechanism, which is a distinct advantage compared with other AI models. Hydrological and large-scale atmospheric circulation variables, including rainfall, streamflow, and atmospheric circulation factors are used to establish models and forecast streamflow for Huanren Reservoir and Xiangjiaba Hydropower Station, China. The artificial neural network (ANN) and extreme learning machine (ELM) with inputs identified based on cross-correlation and mutual information analyses are established for comparative analyses. The performances of these models are assessed with several statistical metrics and graphical evaluation methods. The results show that CNN outperforms ANN and ELM in all statistical measures. Moreover, CNN shows better stability in forecasting accuracy.

     

Simulation of football based on PID controller and BP neural network

Wheel robot soccer speed control system using a ball object detection method and PID controller. A control system is based on the object detection system's behavior based on the robot position's orientation to the target position. PIDs are instruments, pressure, speed, and other operational factors used in control, temperature adjustment flow, and industrial control applications. The PID controller uses control loop feedback dynamics to control functional variables and is the most accurate and stable controller. The robot position is held by placing the ball vertically. When the robot's work is perpendicular to the ball, the robot moves with a certain speed controlled by the PIT controller based on the robot's distance and the ball. Standard conditions (standard ball) test results show that the robot can detect the ball material while in the vertical position, whether on the robot's right or left. In the random test that changes direction, the robot can move more dynamically as the ball's change in place.     

基于SoC的嵌入式DRAM存储器内建自测试设计

内建自测试(Built-in Self Test,BIST)是测试片上系统(System on- Chip,SoC)中嵌入式存储器的重要技术;但是,利用BIST技术采用多种算法对嵌入式存储器进行测试仍面临诸多挑战;对此,提出了一种基于SoC的可以带有多种测试算法的嵌入式DRAM存储器BIST设计,所设计的测试电路可以复用状态机的状态,利用循环移位寄存器(Cyclic Shift Register,CSR)产生操作命令,利用地址产生电路产生所需地址;通过对3种BIST电路支持的算法,全速测试,面积开销3个方面的比较,表明提出的嵌入式DRAM存储器BIST设计在测试时间,测试故障覆盖率和测试面积开销等各方面都取得了较好的性能.     

PUF-enhanced offline RFID security and privacy

RFID (Radio Frequency IDentification) based communication solutions have been widely used nowadays for mobile environments such as access control for secure system, ticketing systems for transportation, and sport events. These systems usually depend on readers that are not continuously connected to a secure backend system. Thus, the readers should be able to perform their duties even in offline mode, which generally requires the management by the readers of the susceptible data. The use of RFID may cause several security and privacy issues such as traceability of tag owner, malicious eavesdropping and cloning of tags. Besides, when a reader is compromised by an adversary, the solution to resolve these issues getting worse. In order to handle these issues, several RFID authentication protocols have been recently proposed; but almost none of them provide strong privacy for the tag owner. On the other hand, several frameworks have been proposed to analyze the security and privacy but none of them consider offline RFID system.Motivated by this need, in this paper, we first revisit Vaudenay's model, extend it by considering offline RFID system and introduce the notion of compromise reader attacks. Then, we propose an efficient RFID mutual authentication protocol. Our protocol is based on the use of physically unclonable functions (PUFs) which provide cost-efficient means to the fingerprint chips based on their physical properties. We prove that our protocol provides destructive privacy for tag owner even against reader attacks.